IEEE.org| IEEE Xplore Digital Library| IEEE Standards| IEEE Spectrum| More Sites

Cart (Loading....) | Create Account | 

Close category search window
Author Searchbeta |  Advanced Search  |  Preferences |  Search Tips  |  More Search Options  
 
Browse Conference Publications > Pattern Recognition, 1992. Vo ... Help

Association of adaptative smoothing and Markovian models for detection of valley bottoms on strongly noisy images [nondestructive testing]

Full Text Sign-In or Purchase

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing! close button
puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Azencott, R. ; Univ. de Paris-Sud, Orsay, France ; Chalmond, B. ; Coldefy, F.

The paper is related to a nondestructive control industrial task: the detection of defects in γ radiographic images. The images are very noisy and have a strong luminosity gradient. The authors adopt a Bayes-Markov model in order to estimate the noise, the gradient and the defects. The proposed model is general and can be used in other situations for detecting valley bottoms in noisy images

Published in:
Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings., 11th IAPR International Conference on

Date of Conference: 30 Aug-3 Sep 1992

Page(s):
327 - 330
Meeting Date :
30 Aug 1992-03 Sep 1992
Print ISBN:
0-8186-2920-7
INSPEC Accession Number:
4310972
Conference Location :
The Hague
Digital Object Identifier :
10.1109/ICPR.1992.201991
Product Type:
Conference Publications

IEEE Account

Purchase Details

Profile Information

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.